The core of selecting graphite blocks for machining lies in balancing machinability, product accuracy, and performance. Key factors to focus on include the grain size, density, hardness, and thermal shock resistance of the graphite. Avoiding issues such as cracks, chipping, and deformation during the machining process is crucial. Firstly, the grain size is a key indicator. Fine-grained graphite (particle size ≤ 5 μm) has a high surface finish and good precision, making it suitable for precision molds, electrodes, and other high-precision components; coarse-grained graphite has high processing efficiency and low cost, suitable for general components with lower precision requirements, but prone to surface roughness and edge damage. Secondly, density and hardness directly affect the processing difficulty and product quality. High-density graphite blocks (1.7-1.9 g/cm³) have a dense structure, are less prone to deformation during processing, and have high product strength, suitable for complex structures and high-precision machining; low-density graphite blocks have a softer texture and lower processing difficulty, but are prone to wear and deformation, suitable for simple structures and non-load-bearing components. At the same time, attention should be paid to the graphite's thermal shock resistance. During machining, heat is generated, and graphite with poor thermal shock resistance is prone to cracks due to temperature changes, so it is necessary to prioritize selecting graphite blocks that have undergone thermal stability treatment. Additionally, the selection of graphite blocks should be based on the machining method and product application. For CNC precision machining, fine-grained, high-density, and high-purity graphite should be preferred; for general cutting machining, medium-coarse-grained and medium-density graphite can be selected to reduce processing costs. During procurement, it is necessary to confirm the uniformity of the graphite blocks to avoid internal pores and impurities that may cause products after processing. At the same time， request processing process suggestions and optimize parameters based on your own processing equipment to improve processing efficiency and product yield.
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